Physics AI ML Engineer for Scientific Computing

Datacontroller Toogeza Ltd.; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Zibra AI is seeking a Machine Learning Engineer - Physics AI to advance compression-aware training and benchmarks on large-scale 3D data. You will work at the intersection of physics-informed ML, scientific computing, and ML systems, benchmarking codecs across architectures and studying training in compressed representations.

You will integrate compressed datasets into PyTorch workflows, design robust benchmarks, and publish findings in technical reports and papers, collaborating with research

Qualifications

• Hands-on experience with Physics AI / scientific machine learning is required.
• Experience training models on simulation or physical-science datasets.
• Strong practical experience with PyTorch and modern deep-learning workflows.
• Familiarity with architectures such as neural operators, mesh GNNs, transformers for physical systems, surrogate models, foundation models for science, PINNs or related methods.

Responsibilities

• Benchmark our compression technology across a wide range of Physics AI architectures and datasets.
• Run large-scale experiments for CFD, turbulence, weather, engineering, and other scientific ML workloads.
• Measure the impact of compression on model convergence, training throughput, GPU utilization, data-loading overhead, storage and network requirements.
• Compare compressed-data training against conventional pipelines and alternative compression methods.
• Research training directly in compressed or partially decoded representations.
• Explore compression-aware sampling, augmentation, tokenization, and model architectures.
• Design rigorous, reproducible benchmark methodology.
• Integrate compressed datasets into PyTorch and distributed training workflows.
• Turn experimental results into product recommendations and research directions.
• Write technical reports, benchmark publications, blog posts, and academic papers.
• Collaborate with external research groups and industrial partners on joint evaluations.

Skills

Physics AI

PyTorch

Python

Scientific computing

Distributed training

Experimental design

Job description

Zibra AI is seeking a Machine Learning Engineer - Physics AI to advance compression-aware training and benchmarks on large-scale 3D data. You will work at the intersection of physics-informed ML, scientific computing, and ML systems, benchmarking codecs across architectures and studying training in compressed representations.

You will integrate compressed datasets into PyTorch workflows, design robust benchmarks, and publish findings in technical reports and papers, collaborating with research